Development of Social and Culture Aspects Pre-service Science Teachers on Learning for Nature of Science

Understanding aspects of the Nature of Science (NOS) for preservice science teachers is one of the essential components to be able to understand Science and its processes. There are seven aspects of NOS: empirical, inference, creative, latent theory, tentative, scientific procedural myths, theories and laws of science, social and cultural dimensions, and their embedding in science. There are 48 preservice science teachers involved in this study. Researchers explored their views about NOS and Indigenous Knowledge (IK) through a validated questionnaire. Results showed that the students' opinions on NOS consisted of empirical, tentative, inference, law, scientific theory, and creativity. Meanwhile, aspects of laden theory, myths of scientific procedures, and social and cultural dimensions embedded with science have not been described by students. Fortunately, the students presented IK as an authentic context based on the culture in science learning. Students express IK ideas: 1) biomedicine (40 students), Biopesticide (2 students), beauty ingredients (2 students), additives (1 student), and supernatural medicine (1 student). Integrating Science and IK as an authentic context in science learning leads IK toward high technology and strengthens NOS aspects. In addition, the assumption that IK has no future is declining.

Bamboo Connection Technology for Lightweight Structures

Bamboo construction is often related to traditional and vernacular architecture, which is found mostly in rural areas, where, for the construction, local people apply diverse techniques learned in an empirical way and passed on from generation to generation. However, in the last years, many modern constructions with bamboo have been developed around the world. At the same time, many connections have been designed for permanent and ephemerals lightweight structures. However, most of them do not have standardization and mechanical testing, because it is expensive or there are no means to do it. Therefore, it is required to create a technology classification for the most used existing connections, starting with the traditional way to join canes until the contemporary connections developed with high technology. In this context, connections are a challenge to be developed, as currently there is no normative in bamboo to follow and create standardization.

The Spread of Cross-Border High-Tech Manufacturing Component Goods in International Trade Integration

The objective of this study is to examine the spread of cross-border trading in determining the firm's production in high-technology manufacturing industries in Indonesia. The spread of cross-border trading in the model is measured by export intensity and alternatively is measured by vertical trade integration. The firm-level data of high-tech industries are implemented in this study. A panel data regression procedure is applied to estimate the model. The estimation results elucidate that vertical trade integration is a significant determinant on affecting firm's production while export intensity is not. This evidence proves that the pattern of cross-border international trade of high-technology industries shifted from exporting finished goods to exporting fragmented products. The export intensity variable is no longer representing the international trade when the firms break-down their production process. The usage of export intensity variable in firms undertaking the vertical trade integration would lead to a misleading conclusion.

APPLICATION OF HIGH-TECH AGRICULTURE BY HOUSEHOLDS IN THE RED RIVER DELTA OF VIETNAM

This study is conducted to model the factors that influence the decision to apply high technology in agricultural production (agricultural production) of farmers in the Red River Delta (RRD), Vietnam. Data used for the study are surveyed in fact 600 households participating in agricultural production in the RRD. The paper uses the Binary Logistic regression analysis method to identify the factors affecting the decision to apply high technology to agricultural production. The research results show that factors such as farm households' education, people's participation in social organizations, the impact of urbanization, capital and market availability all have positive effects extreme decision to apply technology of farmers. Based on the results of the study, the paper proposed policies to be focused on to enhance the application of high technology in agricultural production by farmers. The findings of this study demonstrate that people's application of high technology to agricultural production is improved by enhancing their production capacity.

Optimization of STP Innovation Management Mechanisms Driven by Advanced Evolutionary IoT Arithmetic

Since industrialization, manufacturing has been an important pillar of a country’s economic development. Under the dual pressure of the new trend of global manufacturing development and the loss of competitive advantage of manufacturing industry, it is especially important to accelerate the enhancement of national high technology innovation capacity and the optimization of high technology policy innovation management mechanism driven by advanced evolutionary Internet of Things (IoT) arithmetic. The main of this paper thus introduces the effective method of optimization of high technology policy innovation management mechanism driven by advanced evolutionary IoT arithmetic. To study the optimization of high technology policy innovation management mechanism, a conceptual analysis of currently popular information technologies, such as big data technologies, artificial intelligence technologies, and Internet of Things technologies, and an overview of the application of these technologies in microgrids are given. In the paper, all factors are studied using the STP innovation management mechanism-based approach, and finally, all factors are classified into two categories of cause and effect factors by this approach, and the importance of all factors is ranked. Secondly, a wind power prediction algorithm based on data mining technology and an improved algorithm and a PV power prediction algorithm based on a deep neural network were established with the technical support of high-tech information technology such as big data and artificial intelligence. Finally, the majorization of high technology policy innovation management mechanism driven by advanced evolutionary IoT arithmetic is proposed.